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Mary F. Jones; Julie Dallavis – Journal of Educational Administration, 2024
Purpose: Research shows data-informed leadership matters for school improvement and student achievement, but less is known about what motivates leaders' data use toward such outcomes, particularly in the Catholic school context. Design/methodology/approach: This qualitative interview study uses interview (n = 23) data from a sample of Catholic…
Descriptors: Data Use, Educational Improvement, Catholic Schools, Instructional Leadership
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Yu-Jie Wang; Chang-Lei Gao; Xin-Dong Ye – Education and Information Technologies, 2024
The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…
Descriptors: Precision Teaching, Data Use, Intervention, Educational Improvement
Charles Sanchez; Eleanor Eckerson Peters; Diane Cheng; Sean Tierney – Institute for Higher Education Policy, 2024
For decades, assessing income has served as the tried-and-true method for creating financial aid packages--scholarships, grants, and loans--for the nation's college students. Each year, students and families living with low and moderate incomes submit income documentation to colleges, states, and the federal government in hopes of qualifying for…
Descriptors: Higher Education, Racial Factors, Race, Equal Education
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Putri Dwi Agustiningrum; Wirawan Fadly; Primus Demboh – Journal of Science Learning, 2024
This research aims to develop ECARsites, an online site designed to support data-related activities in science learning and to facilitate the implementation of data, computational thinking (CT), and self-directed learning (SRL) practices in a more contextualized and relevant way for students. The approach used design-based research (DBR) methods,…
Descriptors: Middle School Teachers, Science Teachers, Middle School Students, Faculty Development
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Jinhee Kim – Education and Information Technologies, 2024
Moving beyond the direct support all alone by a human teacher or an Artificial Intelligence (AI) system, optimizing the complementary strengths of the two has aroused great expectations and educational innovation potential. Yet, the conceptual guidance of how best to structure and implement teacher-AI collaboration (TAC) while ensuring teachers'…
Descriptors: Teacher Attitudes, Artificial Intelligence, Man Machine Systems, Curriculum Development
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Olga Agatova; Alexander Popov; Suad Abdalkareem Alwaely – Interactive Learning Environments, 2024
The paper examines the special aspects of using Big Data technology in education. The population was made up of 356 third-year university students. To study Big Data technology, a questionnaire was used where respondents rated: cloud technology; apps; Massive Open Online Courses (MOOCs) and digital learning platforms. The study suggested that the…
Descriptors: Data Use, Learning Processes, Technology Uses in Education, Information Storage
Katherine A. Shields; Bryan C. Hutchins; Kelly Reese; Edward C. Fletcher; Katherine Hughes – Career and Technical Education Research Network, 2024
In recent years, career and technical education (CTE) programs that include quality work-based learning (WBL) opportunities for students have gained significant traction among educators, policymakers, and stakeholders as an effective way to prepare students for the labor market. However, a lack of data on WBL--which many CTE students participate…
Descriptors: Vocational Education, Experiential Learning, Data Collection, Educational Research
Denise Nadasen – Association of Public and Land-grant Universities, 2024
The Data Culture Framework is a high-level guide designed for institutional leaders who want to create and sustain an effective data culture on campus. The Framework offers a set of practices designed to help institutions of higher education create and maintain an effective data-informed community among institutional leaders, faculty, and staff.
Descriptors: Land Grant Universities, Data Collection, Data Use, College Faculty
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Yun Du – International Journal of Web-Based Learning and Teaching Technologies, 2024
This paper deeply discusses the transformation potential of integrating Internet big data into the pre-school education model in colleges and universities. Through in-depth analysis, we studied the challenges and opportunities faced by preschool education in colleges and universities, and discussed the innovative influence of big data technology…
Descriptors: Educational Innovation, Preschool Education, Data Analysis, Data Collection
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Jo B. Helgetun; Mathias Decuypere – Learning, Media and Technology, 2024
This article analyses the smartphone application TeacherTapp that is used to collect and disseminate information on teachers' views on education and their classroom practices. The research takes as its object of analysis the use of TeacherTapp in England and Flanders. We analyze what TeacherTapp is, how it relates to a given localized community in…
Descriptors: Computer Uses in Education, Computer Oriented Programs, Educational Technology, Handheld Devices
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Francesco Fabbro; Elena Gabbi – Journal of Media Literacy Education, 2024
Lately conspiracy theories (CT) are increasingly hovering over Education Studies, mostly as problems in search of a solution. This paper problematizes this educational solutionist discourse by reflecting critically on different framing of CT (i.e., epistemological and ethico-political) and some related educational responses, ranging from…
Descriptors: Misconceptions, Misinformation, Theories, Media Literacy
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Hongyu Xie; He Xiao; Yu Hao – International Journal of Web-Based Learning and Teaching Technologies, 2024
Modern e-learning system is a representative service form in innovative service industry. This paper designs a personalized service domain system, optimizes various parameters and can be applied to different education quality evaluation, and proposes a decision tree recommendation algorithm. Information gain is carried out through many existing…
Descriptors: Artificial Intelligence, Electronic Learning, Individualized Instruction, Models
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Beverly Cheri Neal – International Journal of Educational Administration and Policy Studies, 2024
The purpose of the study was to better understand the extent to which middle school principals' transformational leadership styles affect teachers' data-informed instruction, the influence of teachers' data-informed instruction on middle school student achievement, and the extent to which transformational leaders affect student achievement through…
Descriptors: Transformational Leadership, Data Use, Teaching Methods, Academic Achievement
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John Stamper; Steven Moore; Carolyn P. Rosé; Philip I. Pavlik Jr.; Kenneth Koedinger – Journal of Educational Data Mining, 2024
LearnSphere is a web-based data infrastructure designed to transform scientific discovery and innovation in education. It supports learning researchers in addressing a broad range of issues including cognitive, social, and motivational factors in learning, educational content analysis, and educational technology innovation. LearnSphere integrates…
Descriptors: Learning Analytics, Web Sites, Data Use, Educational Technology
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Kerstin Wagner; Agathe Merceron; Petra Sauer; Niels Pinkwart – Journal of Educational Data Mining, 2024
In this paper, we present an extended evaluation of a course recommender system designed to support students who struggle in the first semesters of their studies and are at risk of dropping out. The system, which was developed in earlier work using a student-centered design, is based on the explainable k-nearest neighbor algorithm and recommends a…
Descriptors: At Risk Students, Algorithms, Foreign Countries, Course Selection (Students)
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